ABSTRACT-Video transmission in a wireless network has been

ABSTRACT-Video transmission in a wireless network has
been available for quite some time and their increasing usage in daily
activities, importantly for work related matters have demanded a stable outlet.
There is no guarantee at the point of reception for the correct ordering of
packets of data, and for processing of data in a smooth manner so that the
video will proceed without interruptions. While there few methods that have
improved transmission greatly, there are still problems like improving the
throughput wireless LAN. In the analysis it has been proved that the layered
approach takes too much time to provide seamless transmission. Thus a cross
layered approach has been adopted in which the focus will be on the physical
layer, the MAC layer and the application layer. Signal to Noise Ratio (SNR) is
a property of wireless networks that is used to measure the most optimum rate
of transmission as there are several transmission rates according to the device
used. The transmission rate will be determined using Rate Adaptation Algorithm.
The transmission rate at the application layer is then synchronized with the
MAC layer using Adaptive Encoding. This proposed analysis will be useful in
measuring the most optimum transmission rates followed by an effective adaptive
encoding process, thereby improving the throughput of IEEE 80211n WLAN.

 

I.                   
INTRODUCTION

 

Yang
Xiao and et all (2013) survey the available cross-layer designs. Classification
is done with respect to two structures one based on the information sharing
between the nodes and other based on the organization of the network. Based on
the information sharing between the nodes it is divided into two categories-
Manager and Non-Manager Method. Manager method uses the Control program which
acts as a transmission medium for sharing information between the layers.
Non-Manager method passes information without any medium creating an illusion
that every layer is adjacent to each other. Based on the organization of the
network it is divided into two types-Distributed method and Centralized method.
The centralized method uses a centralized node or tier which is in a
hierarchical manner to achieve communication between nodes. The centralized
method is typically used in cellular networks. The
distributed method does not use any centralized node or tier. The distributed
method is typically used in ad-hoc networks 1.

 

             Gabriel Martorell et all (2009)
uses a Cross-Layer Fast Link Adaptation (FLA). Optimization is done in both
Transmitter side and Receiver side. An FLA technique based on packet error rate
(PER) that makes use of the exponential effective SNR mapping (EESM) is used.
Additionally, a bit error rate (BER) based FLA scheme is proposed that
simplifies the calibration procedure without any significant performance
degradation. Bit Error Rate in the Physical layer is used to determine the
Packet Error Rate (PER) in which the Modulation and Coding Scheme (MCS) is
selected, having least outage probability. Using PER, instantaneous throughput
of the each MCS is calculated and the MCS with the least value is selected. The
probability is the direct consequence of the objective function

Pm = fm(SNR)

 

The MCS is chosen such that Pm
is minimized. This MCS gives the optimal transmission rate 2.

Rate Adaptation

             Arafet Ben Makhlouf and et all
proposed a Rate Adaptation algorithm called L3S.Rate Adaptation algorithm is
based on a probing system that guarantees that it is has Long-Term Stability
and Short-Term Responsiveness. The new rate adaptation classifies transient and
sustained changes in the link conditions. Then, it controls both short-term and
long-term channel quality variations respectively by monitoring continuously
the transmission history and intelligently probing at new data rates that may
outperform the current rate. Short-term statistics are used to control
transmission rate at short time changes. It uses consecutive received and lost
ACK to determine the channel condition and decide the transmission rate.
Long-term statistics are maintained to adapt transmission rate, which provides
best throughput, against the long sustained changes. Transmission rate is
adapted to senders state .Sender uses two states Tx state and Probe state. In
each round, the transmitter moves periodically between these two states and
updates continuously the associated statistics. Using these states MCS with
high throughput is selected 3

 

             Jiansong Zhang et all (2008) uses
SNR for rate adaptation to counter the rate adaptation techniques which
involves frame losses. These frame losses algorithm doesn’t able to
differentiate channel error and interference losses. In this paper SNR is
considered but SNR is an uncalibrated data so a novel Frame delivery ratio
FDR-SNR bases prediction is uses as FDR as an optimistic optimization of SNR. First step is the online calibration of SNR in which the SNR
low and SNR high is calculated for the current transmission rate. Then the Rate
Adaptation algorithm checks if there is any interference in the channel if so
an interference variable is set or interference free variable is set. If the
interference free variable is set then for each rate available the interference
FDR* is calculated. Else the FDR is calculated as the function of SNR values of
low and high then the rate with maximum FDR is chosen and applied to the network
4.

 

Adaptive encoding

             S.Khan et all (2006) proposed architecture
at the application layer, the video encoder can also adapt to the link quality
by, for example, changing the compression degree and thus modifying the data
rate. This adaptation requires that the video encoder be able to sense the link
quality (e.g., by setting feedback information from the decoder side). An
adaptive encoding technique if used .The video codec used is an H.263 codec
modified to support interaction with the link layer. The H.263 encoder supports
a video rate control algorithm (VRCA) that tries to achieve a certain rate by
adjusting the quantization step size. The quantization step size is the main
parameter that controls the compression of the video. This VRCA has been
designed for constant bit rate (CBR) encoding, but can also be used to dynamically
change the bit rate produced by the encoder 5.